Importance of Store-level POS Data

A recent article in the Los Angeles Times reported on the growing number of electric car charging stations popping up at retailers’ locations. Walgreen Co. plans to install charging stations at 800 of its stores. Macy’s, Best Buy and Kohl’s will also install charging stores — on a much smaller scale than Walgreens — at a limited number of retail test locations.

One has to ask — will the stores with charging stations attract more “green” consumers? The larger question is: how do you capitalize on a trend that doesn’t necessarily have a direct relation to retail? You need store level data.

If, for example, you were looking to capitalize on a green trend you need to determine which stores to target. Start by analyzing the sales of your green items and look for individual stores that have higher sales for green SKUs. Also be certain to set up custom item groups for green items in order to make it easier for you to discover insights. If your business intelligence solution doesn’t allow you to create custom item groups, then assign attributes to the items and view them together in order to determine which stores/groups have higher sales for the green items. Finally, review demographic data — either from your retailer or Nielsen. Certain demographic areas are known to be eco-friendly, but demographic data can help you target green areas that may be otherwise overlooked.

Once you’ve determined the stores to target, it’s time to take advantage of new opportunities. Consider running promotions targeted toward the green consumer. Once you begin running the promotions, review the data to examine specific facets, such as price, to optimize the promotions for this audience. Ads or sales that promote the retailer as a green destination are worth considering as well.

To test new green brands or SKUs, run the product launch trials in your selected green stores. It’s a great way to take advantage of an identified green store persona, without running the risk of launching green products in stores that may not cater to a green demographic.

Having identified green stores, you will also have a better grasp on inventory implications for your green products because you will be able to compare demand at green versus not-so-green stores and adjust your inventory and distribution accordingly. Because you have demand data on hand — and clear trends identified in your green custom store group — you can make a better case with your retailer when it comes to forecasting. Your buyers will be more likely to alter their forecasts for green products if you can clearly demonstrate what particular stores will drive greater green volume.

Finally, one of your greatest opportunities is identifying affinity opportunities. By cross-indexing different attributes, you should be able to identify other SKUs that are popular with green consumers. Do they buy in bulk to reduce packaging waste? Analyze larger-size items to see if there’s a correlation. Do they buy organic items? This is a common affinity, so consider increasing the space for organic foods and natural beauty products on the shelves. Do green consumers buy more fresh foods or all-natural items? By using your business intelligence solution to attribute items specifically by their features, you can easily group SKUs together and analyze trends. The correlations between different attributes can be limitless!